Hugo Larochelle

According to our database1, Hugo Larochelle authored at least 97 papers between 2005 and 2018.

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Bibliography

2018
Traffic Analytics With Low-Frame-Rate Videos.
IEEE Trans. Circuits Syst. Video Techn., 2018

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.
CoRR, 2018

Meta-Learning for Semi-Supervised Few-Shot Classification.
CoRR, 2018

Disentangling the independently controllable factors of variation by interacting with the world.
CoRR, 2018

2017
Domain-Adversarial Training of Neural Networks.
Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

Brain tumor segmentation with Deep Neural Networks.
Medical Image Analysis, 2017

Document Neural Autoregressive Distribution Estimation.
Journal of Machine Learning Research, 2017

Movie Description.
International Journal of Computer Vision, 2017

HoME: a Household Multimodal Environment.
CoRR, 2017

Modulating early visual processing by language.
CoRR, 2017

Multiscale sequence modeling with a learned dictionary.
CoRR, 2017

Modulating early visual processing by language.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Meta-Learning Perspective on Cold-Start Recommendations for Items.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learn to Track: Deep Learning for Tractography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

GuessWhat?! Visual Object Discovery through Multi-modal Dialogue.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Deep Learning Trends for Focal Brain Pathology Segmentation in MRI.
Proceedings of the Machine Learning for Health Informatics, 2016

A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

An Infinite Restricted Boltzmann Machine.
Neural Computation, 2016

Correlational Neural Networks.
Neural Computation, 2016

Neural Autoregressive Distribution Estimation.
Journal of Machine Learning Research, 2016

Domain-Adversarial Training of Neural Networks.
Journal of Machine Learning Research, 2016

GuessWhat?! Visual object discovery through multi-modal dialogue.
CoRR, 2016

Neural Autoregressive Distribution Estimation.
CoRR, 2016

Movie Description.
CoRR, 2016

Document Neural Autoregressive Distribution Estimation.
CoRR, 2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.
CoRR, 2016

Deep learning trends for focal brain pathology segmentation in MRI.
CoRR, 2016

Hierarchical Memory Networks.
CoRR, 2016

Recurrent Mixture Density Network for Spatiotemporal Visual Attention.
CoRR, 2016

Within-brain classification for brain tumor segmentation.
Int. J. Computer Assisted Radiology and Surgery, 2016

Autoencoding beyond pixels using a learned similarity metric.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Dynamic Capacity Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Guest Editorial: Deep Learning for Multimedia Computing.
IEEE Trans. Multimedia, 2015

A Neural Autoregressive Approach to Attention-based Recognition.
International Journal of Computer Vision, 2015

Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism.
CoRR, 2015

Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research.
CoRR, 2015

Within-Brain Classification for Brain Tumor Segmentation.
CoRR, 2015

Brain Tumor Segmentation with Deep Neural Networks.
CoRR, 2015

MADE: Masked Autoencoder for Distribution Estimation.
CoRR, 2015

Domain-Adversarial Training of Neural Networks.
CoRR, 2015

An Infinite Restricted Boltzmann Machine.
CoRR, 2015

Correlational Neural Networks.
CoRR, 2015

Dynamic Capacity Networks.
CoRR, 2015

A Convolutional Neural Network Approach to Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015

Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

MADE: Masked Autoencoder for Distribution Estimation.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Describing Videos by Exploiting Temporal Structure.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data.
CoRR, 2014

An Autoencoder Approach to Learning Bilingual Word Representations.
CoRR, 2014

Learning Multilingual Word Representations using a Bag-of-Words Autoencoder.
CoRR, 2014

Sequential Model-Based Ensemble Optimization.
CoRR, 2014

Domain-Adversarial Neural Networks.
CoRR, 2014

Sequential Model-Based Ensemble Optimization.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

An Autoencoder Approach to Learning Bilingual Word Representations.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Leveraging user libraries to bootstrap collaborative filtering.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

A Deep and Tractable Density Estimator.
Proceedings of the 31th International Conference on Machine Learning, 2014

Agnostic Bayesian Learning of Ensembles.
Proceedings of the 31th International Conference on Machine Learning, 2014

Topic Modeling of Multimodal Data: An Autoregressive Approach.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Guest Editors' Introduction: Special Section on Learning Deep Architectures.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation
CoRR, 2013

A Deep and Tractable Density Estimator.
CoRR, 2013

NADE: The real-valued neural autoregressive density-estimator.
CoRR, 2013

RNADE: The real-valued neural autoregressive density-estimator.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Learning Where to Attend with Deep Architectures for Image Tracking.
Neural Computation, 2012

Nonparametric guidance of autoencoder representations using label information.
Journal of Machine Learning Research, 2012

On Nonparametric Guidance for Learning Autoencoder Representations.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Learning Algorithms for the Classification Restricted Boltzmann Machine.
Journal of Machine Learning Research, 2012

Practical Bayesian Optimization of Machine Learning Algorithms
CoRR, 2012

Training Restricted Boltzmann Machines on Word Observations
CoRR, 2012

Conditional Restricted Boltzmann Machines for Structured Output Prediction
CoRR, 2012

Detonation Classification from acoustic Signature with the Restricted Boltzmann Machine.
Computational Intelligence, 2012

Practical Bayesian Optimization of Machine Learning Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Neural Autoregressive Topic Model.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Training Restricted Boltzmann Machines on Word Observations.
Proceedings of the 29th International Conference on Machine Learning, 2012

Learning to rank by aggregating expert preferences.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
The Neural Autoregressive Distribution Estimator.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Learning where to Attend with Deep Architectures for Image Tracking
CoRR, 2011

Loss-sensitive Training of Probabilistic Conditional Random Fields
CoRR, 2011

Classification of Sets using Restricted Boltzmann Machines
CoRR, 2011

Autotagging music with conditional restricted Boltzmann machines
CoRR, 2011

Conditional Restricted Boltzmann Machines for Structured Output Prediction.
Proceedings of the UAI 2011, 2011

Classification of Sets using Restricted Boltzmann Machines.
Proceedings of the UAI 2011, 2011

Learning attentional policies for tracking and recognition in video with deep networks.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest.
Neural Computation, 2010

Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion.
Journal of Machine Learning Research, 2010

Efficient Learning of Deep Boltzmann Machines.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Learning to combine foveal glimpses with a third-order Boltzmann machine.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Deep Learning using Robust Interdependent Codes.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Exploring Strategies for Training Deep Neural Networks.
Journal of Machine Learning Research, 2009

2008
Extracting and composing robust features with denoising autoencoders.
Proceedings of the Machine Learning, 2008

Classification using discriminative restricted Boltzmann machines.
Proceedings of the Machine Learning, 2008

Zero-data Learning of New Tasks.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
An empirical evaluation of deep architectures on problems with many factors of variation.
Proceedings of the Machine Learning, 2007

2006
Nonlocal Estimation of Manifold Structure.
Neural Computation, 2006

Greedy Layer-Wise Training of Deep Networks.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005
Non-Local Manifold Parzen Windows.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005


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